The selection of the most probable dependency structure in Japanese using mutual information

Authors:
Eduardo de Paiva Alves
Affiliations:
University of Electro-Communications, Chofugaoka, Chofushi, Tokyo, Japan
Venue:
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Year:
1996

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Structural disambiguation based on reliable estimation of strength of association

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2

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Abstract

We use a statistical method to select the most probable structure or parse for a given sentence. It takes as input the dependency structures generated for the sentence by a dependency grammar, finds all triple of modifier, particle and modificant relations, calculates mutual information of each relation and chooses the structure for which the product of the mutual information of its relations is the highest.